The DOI matches its Crossref record; 91 of the 91 references it cites were found in a registry or an index.
Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects
Open accessAbstract
Remote sensing provides a broad view of landscapes and can be consistent through time, making it an important tool for monitoring and managing protected areas. An impediment to broader use of remote sensing science for monitoring has been the need for resource managers to understand the specialized capabilities of an ever-expanding array of image sources and analysis techniques. Here, we provide guidelines that will enable land managers to more effectively collaborate with remote sensing scientists to develop and apply remote sensing science to achieve monitoring objectives. We first describe fundamental characteristics of remotely sensed data and change detection analysis that affect the types and range of phenomena that can be tracked. Using that background, we describe four general steps in natural resource remote sensing projects: image and reference data acquisition, pre-processing, analysis, and evaluation. We emphasize the practical considerations that arise in each of these steps. We articulate a four-phase process that guides natural resource and remote sensing specialists through a collaborative process to articulate goals, evaluate data and options for image processing, refine or eliminate unrealistic paths, and assess the cost and utility of different options.
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Cites
Red and photographic infrared linear combinations for monitoring vegetation
Tucker, C. J. (1979) · Remote Sensing of Environment · doi:10.1016/0034-4257(79)90013-0 · Cited by 11,754
Assessing the Accuracy of Remotely Sensed Data: Principles and Practices
Congalton, R., & Green, K. (1998) · Mapping Science · doi:10.1201/9781420048568 · Cited by 3,424
Lu, D., Mausel, P., Brondízio, E., & Moran, E. (2004) · International Journal of Remote Sensing · doi:10.1080/0143116031000139863 · Cited by 3,226
Assessing the Accuracy of Remotely Sensed Data: Principles and Practices
Foody, G. (2010) · The Photogrammetric Record · doi:10.1111/j.1477-9730.2010.00574_2.x · Cited by 2,806
Remote Sensing Digital Image Analysis: An Introduction
Richards, J. A., & Jia, X. (2006) · Springer eBooks · doi:10.1007/3-540-29711-1 · Cited by 2,759
Radar interferometry and its application to changes in the Earth's surface
Massonnet, D., & Feigl, K. L. (1998) · Reviews of Geophysics · doi:10.1029/97rg03139 · Cited by 2,624
Introduction to remote sensing
Campbell, J. B. (1987) · Geocarto International · doi:10.1080/10106048709354126 · Cited by 2,292
Remote sensing, models, and methods for image processing
Schowengerdt, R. A. (1997) · Cited by 2,122
Review ArticleDigital change detection methods in ecosystem monitoring: a review
Coppin, P., Jonckheere, I., Nackaerts, K., Muys, B., & Lambin, E. (2004) · International Journal of Remote Sensing · doi:10.1080/0143116031000101675 · Cited by 2,100
A Landsat Surface Reflectance Dataset for North America, 1990–2000
Masek, J. G., Vermote, E. F., Saleous, N. E., Wolfe, R., Hall, F. G., Huemmrich, K. F., Gao, F., Kutler, J., & Lim, T.-K. (2006) · IEEE Geoscience and Remote Sensing Letters · doi:10.1109/lgrs.2005.857030 · Cited by 1,627
Cited by
Change detection from remotely sensed images: From pixel-based to object-based approaches
Hussain, M., Chen, D., Cheng, A., Wei, H., & Stanley, D. (2013) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/j.isprsjprs.2013.03.006 · Cited by 1,508
Opening the archive: How free data has enabled the science and monitoring promise of Landsat
Wulder, M. A., Masek, J. G., Cohen, W. B., Loveland, T. R., & Woodcock, C. E. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.01.010 · Cited by 1,206
Self-citationA comprehensive change detection method for updating the National Land Cover Database to circa 2011
Jin, S., Yang, L., Danielson, P., Homer, C., Fry, J., & Xian, G. (2013) · Remote Sensing of Environment · doi:10.1016/j.rse.2013.01.012 · Cited by 699
Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images
Du, B., Ru, L., Wu, C., & Zhang, L. (2019) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2019.2930682 · Cited by 319
Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring
Hermosilla, T., Wulder, M. A., White, J. C., Coops, N. C., Hobart, G. W., & Campbell, L. B. (2016) · International Journal of Digital Earth · doi:10.1080/17538947.2016.1187673 · Cited by 293
Metadata
- Authors
- Kennedy, R. E., Townsend, P. A., Gross, J. E., Cohen, W. B., Bolstad, P., Wang, Y. Q., & Adams, P.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2009-07
- Volume
- 113
- Issue
- 7
- Pages
- 1382-1396
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2107450528
- Cited by
- 411
- References
- 91
- FWCI
- 39.37
- Type
- journal article
- Language
- en
- Open access
- green
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- Kennedy, R. E., Townsend, P. A., Gross, J. E., Cohen, W. B., Bolstad, P., Wang, Y. Q., & Adams, P. (2009). Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2008.07.018
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